Copy number variation and variant discovery in Bullmastiff dogs

Identification of genomic variants within dogs is important for understanding genetic factors contributing to breed diversity and phenotypic traits. This study aimed to identify sources of variation in the Bullmastiff using high‐density signal intensity and whole‐genome sequence data. Close to 3000 copy number variants (CNVs) were identified in Bullmastiff dogs using Canine HD BeadChip data. When CNVs were collated, 82 CNV regions (CNVRs) were detected, 50% in transcribed regions encompassing 432 genes. Fifty of the CNVRs detected have not been reported in other breeds and represent potential breed‐specific variants. A proportion of the CNVR variants with predicted modifying effects on gene pathways may contribute to breed traits. Approximately 5 million putative variants per dog, inclusive of single nucleotide polymorphisms (SNPs), multi‐nucleotide polymorphisms (MNPs) and insertion and deletions (INDELs), were identified from DNA sequence data on a small number of animals. Identification of genetic variants in the Bullmastiff highlights sources of variation in the breed and molecular markers that will assist in future trait and disease investigations in dogs.     

A comprehensive biomedical variant catalogue based on whole genome sequences of 582 dogs and eight wolves

The domestic dog serves as an excellent model to investigate the genetic basis of disease. More than 400 heritable traits analogous to human diseases have been described in dogs. To further canine medical genetics research, we established the Dog Biomedical Variant Database Consortium (DBVDC) and present a comprehensive list of functionally annotated genome variants that were identified with whole genome sequencing of 582 dogs from 126 breeds and eight wolves. The genomes used in the study have a minimum coverage of 10× and an average coverage of ~24×. In total, we identified 23 133 692 single‐nucleotide variants (SNVs) and 10 048 038 short indels, including 93% undescribed variants. On average, each individual dog genome carried ～4.1 million single‐nucleotide and ~1.4 million short‐indel variants with respect to the reference genome assembly. About 2% of the variants were located in coding regions of annotated genes and loci. Variant effect classification showed 247 141 SNVs and 99 562 short indels having moderate or high impact on 11 267 protein‐coding genes. On average, each genome contained heterozygous loss‐of‐function variants in 30 potentially embryonic lethal genes and 97 genes associated with developmental disorders. More than 50 inherited disorders and traits have been unravelled using the DBVDC variant catalogue, enabling genetic testing for breeding and diagnostics. This resource of annotated variants and their corresponding genotype frequencies constitutes a highly useful tool for the identification of potential variants causative for rare inherited disorders in dogs.     

Genomewide discovery of DNA polymorphisms in rice cultivars with contrasting drought and salinity stress response and their functional relevance

Next‐generation sequencing technologies provide opportunities to understand the genetic basis of phenotypic differences, such as abiotic stress response, even in the closely related cultivars via identification of large number of DNA polymorphisms. We performed whole‐genome resequencing of three rice cultivars with contrasting responses to drought and salinity stress (sensitive IR64, drought‐tolerant Nagina 22 and salinity‐tolerant Pokkali). More than 356 million 90‐bp paired‐end reads were generated, which provided about 85% coverage of the rice genome. Applying stringent parameters, we identified a total of 1 784 583 nonredundant single‐nucleotide polymorphisms (SNPs) and 154 275 InDels between reference (Nipponbare) and the three resequenced cultivars. We detected 401 683 and 662 509 SNPs between IR64 and Pokkali, and IR64 and N22 cultivars, respectively. The distribution of DNA polymorphisms was found to be uneven across and within the rice chromosomes. One‐fourth of the SNPs and InDels were detected in genic regions, and about 3.5% of the total SNPs resulted in nonsynonymous changes. Large‐effect SNPs and InDels, which affect the integrity of the encoded protein, were also identified. Further, we identified DNA polymorphisms present in the differentially expressed genes within the known quantitative trait loci. Among these, a total of 548 SNPs in 232 genes, located in the conserved functional domains, were identified. The data presented in this study provide functional markers and promising target genes for salinity and drought tolerance and present a valuable resource for high‐throughput genotyping and molecular breeding for abiotic stress traits in rice.     

Identification of genetic variants associated with maize flowering time using an extremely large multi‐genetic background population

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi‐ genetic background population that contained more than 8000 lines under multiple Sino‐United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single‐nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One‐third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome‐wide association study of the three panels identified nearly 1000 flowering time‐associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs – one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.     

A survey of genome‐wide single nucleotide polymorphisms through genome resequencing in the Périgord black truffle (Tuber melanosporum Vittad.)

The Périgord black truffle (Tuber melanosporum Vittad.), considered a gastronomic delicacy worldwide, is an ectomycorrhizal filamentous fungus that is ecologically important in Mediterranean French, Italian and Spanish woodlands. In this study, we developed a novel resource of single nucleotide polymorphisms (SNPs) for T. melanosporum using Illumina high‐throughput resequencing. The genome from six T. melanosporum geographical accessions was sequenced to a depth of approximately 20×. These geographical accessions were selected from different populations within the northern and southern regions of the geographical species distribution. Approximately 80% of the reads for each of the six resequenced geographical accessions mapped against the reference T. melanosporum genome assembly, estimating the core genome size of this organism to be approximately 110 Mbp. A total of 442 326 SNPs corresponding to 3540 SNPs/Mbps were identified as being included in all seven genomes. The SNPs occurred more frequently in repeated sequences (85%), although 4501 SNPs were also identified in the coding regions of 2587 genes. Using the ratio of nonsynonymous mutations per nonsynonymous site (pN) to synonymous mutations per synonymous site (pS) and Tajima's D index scanning the whole genome, we were able to identify genomic regions and genes potentially subjected to positive or purifying selection. The SNPs identified represent a valuable resource for future population genetics and genomics studies.     

Genome‐wide association studies for hematological traits in swine

Improving immune capacity may increase the profitability of animal production if it enables animals to better cope with infections. Hematological traits play pivotal roles in animal immune capacity and disease resistance. Thus far, few studies have been conducted using a high‐density swine SNP chip panel to unravel the genetic mechanism of the immune capability in domestic animals. In this study, using mixed model‐based single‐locus regression analyses, we carried out genome‐wide association studies, using the Porcine SNP60 BeadChip, for immune responses in piglets for 18 hematological traits (seven leukocyte traits, seven erythrocyte traits, and four platelet traits) after being immunized with classical swine fever vaccine. After adjusting for multiple testing based on permutations, 10, 24, and 77 chromosome‐wise significant SNPs were identified for the leukocyte traits, erythrocyte traits, and platelet traits respectively, of which 10 reached genome‐wise significance level. Among the 53 SNPs for mean platelet volume, 29 are located in a linkage disequilibrium block between 32.77 and 40.59 Mb on SSC6. Four genes of interest are located within the block, providing genetic evidence that this genomic segment may be considered a candidate region relevant to the platelet traits. Other candidate genes of interest for red blood cell, hemoglobin, and red blood cell volume distribution width also have been found near the significant SNPs. Our genome‐wide association study provides a list of significant SNPs and candidate genes that offer valuable information for future dissection of molecular mechanisms regulating hematological traits.     

Genome‐wide association study identifies quantitative trait loci affecting hematological traits in an F2 intercross between Landrace and Korean native pigs

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome‐wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F₂ progeny were analyzed for each blood‐related trait after filtering for quality control. Data were analyzed by the genome‐wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10^?6) on SSC3, 6, 8, 13 and 17 were identified for blood‐related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.     

De novo genome assembly of the stress tolerant forest species Casuarina equisetifolia provides insight into secondary growth

Casuarina equisetifolia (C. equisetifolia), a conifer‐like angiosperm with resistance to typhoon and stress tolerance, is mainly cultivated in the coastal areas of Australasia. C. equisetifolia, making it a valuable model to study secondary growth associated genes and stress‐tolerance traits. However, the genome sequence is unavailable and therefore wood‐associated growth rate and stress resistance at the molecular level is largely unexplored. We therefore constructed a high‐quality draft genome sequence of C. equisetifolia by a combination of Illumina second‐generation sequencing reads and Pacific Biosciences single‐molecule real‐time (SMRT) long reads to advance the investigation of this species. Here, we report the genome assembly, which contains approximately 300 megabases (Mb) and scaffold size of N50 is 1.06 Mb. Additionally, gene annotation, assisted by a combination of prediction and RNA‐seq data, generated 29 827 annotated protein‐coding genes and 1983 non‐coding genes, respectively. Furthermore, we found that the total number of repetitive sequences account for one‐third of the genome assembly. Here we also construct the genome‐wide map of DNA modification, such as two novel forms N⁶‐adenine (6mA) and N4‐methylcytosine (4mC) at the level of single‐nucleotide resolution using single‐molecule real‐time (SMRT) sequencing. Interestingly, we found that 17% of 6mA modification genes and 15% of 4mC modification genes also included alternative splicing events. Finally, we investigated cellulose, hemicellulose, and lignin‐related genes, which were associated with secondary growth and contained different DNA modifications. The high‐quality genome sequence and annotation of C. equisetifolia in this study provide a valuable resource to strengthen our understanding of the diverse traits of trees.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

QTL‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co‐occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole‐genome resequencing (WGRS)‐based approach referred as ‘QTL‐seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference‐guided resistant parent assembly identified 3136 single‐nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL‐seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.     

Genomic variation at the tips of the adaptive radiation of Darwin's finches

Adaptive radiation unfolds as selection acts on the genetic variation underlying functional traits. The nature of this variation can be revealed by studying the tips of an ongoing adaptive radiation. We studied genomic variation at the tips of the Darwin's finch radiation; specifically focusing on polymorphism within, and variation among, three sympatric species of the genus Geospiza. Using restriction site‐associated DNA (RAD‐seq), we characterized 32 569 single‐nucleotide polymorphisms (SNPs), from which 11 outlier SNPs for beak and body size were uncovered by a genomewide association study (GWAS). Principal component analysis revealed that these 11 SNPs formed four statistically linked groups. Stepwise regression then revealed that the first PC score, which included 6 of the 11 top SNPs, explained over 80% of the variation in beak size, suggesting that selection on these traits influences multiple correlated loci. The two SNPs most strongly associated with beak size were near genes associated with beak morphology across deeper branches of the radiation: delta‐like 1 homologue (DLK1) and high‐mobility group AT‐hook 2 (HMGA2). Our results suggest that (i) key adaptive traits are associated with a small fraction of the genome (11 of 32 569 SNPs), (ii) SNPs linked to the candidate genes are dispersed throughout the genome (on several chromosomes), and (iii) micro‐ and macro‐evolutionary variation (roots and tips of the radiation) involve some shared and some unique genomic regions.     

Synonymous SNPs Provide Evidence for Selective Constraint on Human Exonic Splicing Enhancers

The human SNP database was used to detect selection on 238 hexamers previously identified as exonic splicing enhancers (ESEs). We compared the distribution of the 238 putative ESEs in biallelic and triallelic SNPs within five different functional categories of the SNP database: synonymous, nonsynonymous, introns, UTRs, and nongenic SNPs. Since true ESEs do not function outside of exons, SNPs that disrupt ESE motifs were expected to be more common in nonexonic portions of the genome. Our results supported this expectation: ESEs were least prevalent within synonymous SNPs and most common in nongenic SNPs. There were ∼11% fewer ESEs within synonymous biallelic SNPs than expected under no selective constraint. We also compared the frequency of neutral SNPs, those where neither allele was an ESE, with deleterious SNPs, those where one or more alleles was an ESE, across the five different functional classes of SNPs. In comparison with the other functional classes of SNPs, synonymous SNPs contained an excess of neutral variants (+1.64% and +6.04% for biallelic and triallelic SNPs, respectively) and a dearth of deleterious variants (−13.11% and −52.39% for biallelic and triallelic SNPs, respectively). The observed patterns were consistent with purifying selection on the 238 hexamers to maintain their function as ESEs. However, in contrast to previous work, we did not find evidence for selection to maintain ESE function at nonsynonymous SNPs because selection at the protein level probably obscured any difference at the level of ESE function.     

Dissection of the genetic architecture of three seed‐quality traits and consequences for breeding in Brassica napus

Genome‐wide association studies (GWASs) combining high‐throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed‐quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well‐characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed‐quality traits, which would be useful for genetic improvement of B. napus.     

Whole‐genome resequencing of extreme phenotypes in collared flycatchers highlights the difficulty of detecting quantitative trait loci in natural populations

Dissecting the genetic basis of phenotypic variation in natural populations is a long‐standing goal in evolutionary biology. One open question is whether quantitative traits are determined only by large numbers of genes with small effects, or whether variation also exists in large‐effect loci. We conducted genomewide association analyses of forehead patch size (a sexually selected trait) on 81 whole‐genome‐resequenced male collared flycatchers with extreme phenotypes, and on 415 males sampled independent of patch size and genotyped with a 50K SNP chip. No SNPs were genomewide statistically significantly associated with patch size. Simulation‐based power analyses suggest that the power to detect large‐effect loci responsible for 10% of phenotypic variance was <0.5 in the genome resequencing analysis, and <0.1 in the SNP chip analysis. Reducing the recombination by two‐thirds relative to collared flycatchers modestly increased power. Tripling sample size increased power to >0.8 for resequencing of extreme phenotypes (N = 243), but power remained <0.2 for the 50K SNP chip analysis (N = 1245). At least 1 million SNPs were necessary to achieve power >0.8 when analysing 415 randomly sampled phenotypes. However, power of the 50K SNP chip to detect large‐effect loci was nearly 0.8 in simulations with a small effective population size of 1500. These results suggest that reliably detecting large‐effect trait loci in large natural populations will often require thousands of individuals and near complete sampling of the genome. Encouragingly, far fewer individuals and loci will often be sufficient to reliably detect large‐effect loci in small populations with widespread strong linkage disequilibrium.     

A whole genome sequence association study for puberty in a large Duroc × Erhualian F2 population

A large proportion of gilts and sows are culled from reproduction populations because of anestrus and pubertal reproductive failure. Selecting early onset of puberty gilts has a favorable effect on sows’ reproductivity. However, age at puberty is hard to be routinely measured in commercial herds. With molecular genetic predictors, identifying individuals that have a propensity for early onset of puberty can be simplified. We previously performed genome scanning and a genome‐wide association study for puberty in an F2 resource population using 183 microsatellites and 62 125 SNPs respectively. The detection power and resolution of identified quantitative trait loci were very low. Herein, we re‐sequenced 19 founders of the F2 resource population in high coverage, and whole genome sequences of F2 individuals were imputed to perform an association study for reproductive traits. A total of 2339 SNPs associated with pubertal reproductive failure were identified in the region of 30.94–40.74 Mb on SSC7, with the top one, positioned at 33.36 Mb, explaining 16% of the phenotypic variances. We improved the magnitude of the P‐value by 10E+5 to 10E+7 using the whole genome sequence rather than using low/middle density markers as in previous studies, and we narrowed down the QTL confidence interval to 5.25 Mb. Combining the annotation of gene function, RAB23 and BAK1 were perceived as the most compelling candidate genes. The identified loci may be useful in culling sows failing to show estrus by marker‐assisted selection to increase reproductive efficiency of swine herds.     

Single‐nucleotide polymorphism discovery in Leptographium longiclavatum,a mountain pine beetle‐associated symbiotic fungus,using whole‐genome resequencing

Single‐nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost‐effective approaches to uncover genome‐wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole‐genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N₅₀ = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17 266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina^® Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species.